Materials Manufacturing QC (six-sigma)

Common Challenges

• Manufacturing processes can go wrong leading to failed batches, customer complaints and expensive recovery schemes

• Materials/Production data can provide insights that can deliver early problem detection, but data needs to be shared effectively between R&D and manufacturing/operations.

• Lack of a centralized system that monitors and stores data from different quality control (QC) stations in the production line.

• Lack of alerts in case one of the metrics goes out of spec.

• No predictions and alerts in case one of the metrics is expected to be out of spec down the line or in the future.

The value proposition of MaterialsZone

• Merge of R&D data with manufacturing data results in better flow of knowledge between departments.

• Detects and spots failed batches as early as possible, even before they are considered “failed”.

• Find and repair “root cause” of failures.

• One platform, all the data, all the insights, all the stakeholders (R&D, scale-up, manufacturing QC, supply chain alternatives selection).

• Easily applied AI/ML visualizations, insights and predictability.

• No loss of knowledge.

• Rapid accumulation of knowledge and predictability.

What does it take from a Materials Informatics Platform (MIP)?

• Flexible data model that supports multiple dimensions, multiple types of data and any hierarchical nesting and association inherent in materials data.

• Automated data harvesting including calculations and ingestion directly from instruments in QC stations in any type of file (spreadsheet, PDF, binary, graphical, etc.).

• Automated data harvesting loads as AI/ML ready - very easy to slice and dice without the need of data scientists or any preparations.

• Automatic monitoring of important metrics and alerts out of spec metrics.

• Flexibility to accumulate data incrementally and continuously while the AI/ML insights and visualizations update as well.

MaterialsZone provides a great solution for materials manufacturing QC (six-sigma)

MaterialsZone allows materials manufacturing QC (six-sigma) by collecting manufacturing data from the production line. Once the manufacturing data is collected from the various stations along the line and stored in a well structured manner, MaterialsZone can automatically monitor various parameters simultaneously.

Materials manufacturing QC (six-sigma) parameters can be visualized vs time to inspect un-regular behaviors as shown in figure 1.

Figure 1: battery cathode thickness vs time.

In addition to visualizing, MaterialsZone is doing behind the scenes work and alerts in case any of the monitored parameters go out of spec.

The next leap in materials manufacturing QC (six-sigma) is to detect a potential out of spec that is expected to happen either in the following stations down the line or that is expected to happen on the same station in the coming batches.

MaterialsZone can be a one-stop shop for monitoring your materials manufacturing QC (six-sigma).


No items found.